With communications underpinning and documenting organizational behaviors and how perceptions are shaped, it is unsurprising that scholars from a wide array of theoretical orientations have drawn on textual data to capture concepts of interest (e.g., Yoon and Park, 2004;Kennedy, 2005;Chatterjee and Hambrick, 2007), and that there is considerable scholarly interest in understanding organizational communication itself (e.g., Boje, 1991;Elsbach, 2006;Sillince, Jarzabkowski, and Shaw, 2012;Kahl and Grodal, 2016).​However, while communication underpins a substantial proportion of organizational theory and theoretical constructs, and a wealth of textual information is now easily available for researchers, the ability of researchers to systematically extract meaning from this information, or construct variables that closely map to concepts of theoretical interest, is limited. While qualitative studies give significant consideration to the content and form of firm communications (e.g., Martin et al., 1983;Elsbach, 1994;Fiol, 2002), more quantitative approaches often reduce complex, multifaceted theoretical concepts, to a list of keywords, the frequency of which are then counted. Although a particular dimension of meaning may be captured via vocabularies (Tausczik and Pennebaker, 2010;Loewenstein, Ocasio, and Jones, 2012), word usage is nevertheless just one lens through which language can be characterized (Fairclough, 1992), and the approach quickly becomes unfeasible for understanding complex ideas or how these complex ideas evolve over time.

Although there is growing computational linguistics research on ways in which textual communications can be analyzed (e.g., Chowdhury, 2003;Aggarwal and Zhai, 2012), and certain fields such as biology and medicine have seen considerable interest in standardizing and extracting textual information (Cohen and Hersh, 2005;Simpson and Demner-Fushman, 2012;Lacey et al., 2017), there has been very little consideration of the ways in which computational linguistics can yield new theoretical insight in strategy and management research, nor has there been a cumulative effort to systematically capture the spectrum of relationships discussed by firms in their communications.

Menai Insight is developing a platform of analysis tools to transform the texts of organizational communications into consistent representations, that capture the detail of the texts, while preserving the form and structure of the material. These textual structures make it possible to easily aggregate, and compare the nature and form of the communications, facilitating the development of constructs that closely map to variables of theoretical interest. ​

Gareth Keeves received a PhD in strategy from the Ross School of Business, University of Michigan. His research includes impression formation and management in the context of corporate leadership. As the CEO of Menai Insight he is developing approaches for capturing and representing meaning for corporate governance communications. ​